MCPfinder

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries full burden for behavioral disclosure. It states the tool retrieves information (implying read-only), but doesn't clarify if it requires authentication, has rate limits, what happens if the server doesn't exist, or the format of returned data. For a tool with zero annotation coverage, this is insufficient behavioral context.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, efficient sentence that directly states the tool's purpose without unnecessary words. It's appropriately sized for a simple lookup tool and front-loaded with the core functionality.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given no annotations and no output schema, the description is incomplete for a tool that presumably returns structured data. It doesn't explain what 'detailed information' includes, potential error conditions, or response format. For a lookup tool with these gaps, more context is needed to be fully helpful.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema has 100% description coverage, with the 'name' parameter clearly documented as 'Exact name of the MCP server to look up'. The description doesn't add any parameter details beyond what the schema provides, such as format examples or constraints. Baseline 3 is appropriate when the schema does all the work.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose with a specific verb ('Get') and resource ('detailed information about a specific MCP server'). It distinguishes from sibling tools like 'list_trending_servers' and 'search_mcp_servers' by focusing on a single server rather than multiple servers. However, it doesn't explicitly mention what 'detailed information' includes, which prevents a perfect score.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., needing to know the server name), contrast with siblings like 'search_mcp_servers' for unknown names, or specify use cases. This leaves the agent without context for tool selection.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries full burden but offers minimal behavioral insight. It implies a read operation but doesn't disclose details like rate limits, authentication needs, data freshness, or what 'trending' means (e.g., based on downloads, activity). This is inadequate for a tool with zero annotation coverage.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, efficient sentence that directly states the tool's purpose without any fluff. It's appropriately sized and front-loaded, with every word contributing to clarity.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the lack of annotations and output schema, the description is incomplete. It doesn't explain what 'trending' entails, the return format, or how results are ordered, leaving significant gaps for a tool that likely returns structured data.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The schema description coverage is 100%, with the single parameter 'limit' well-documented in the schema. The description adds no parameter-specific information beyond what the schema provides, so it meets the baseline for high schema coverage without adding value.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the action ('Get a list') and resource ('trending MCP servers'), making the purpose immediately understandable. However, it doesn't differentiate this tool from its sibling 'search_mcp_servers', which might also return lists of servers, so it misses the highest score.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus alternatives like 'search_mcp_servers' or 'get_mcp_server_details'. There's no mention of context, prerequisites, or exclusions, leaving the agent to guess based on tool names alone.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries full burden but only states the basic action without disclosing behavioral traits. It doesn't mention aspects like rate limits, authentication needs, pagination, or what happens on no results (e.g., returns empty list or error). For a search tool with zero annotation coverage, this is a significant gap.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, efficient sentence that directly states the tool's purpose without unnecessary words. It is front-loaded and wastes no space, making it highly concise and well-structured.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the complexity of a search tool with 4 parameters and no annotations or output schema, the description is incomplete. It lacks details on return values (e.g., structure of results), error handling, or behavioral context, which are crucial for effective use by an AI agent.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema has 100% description coverage, documenting all parameters (tag, limit, query, capability) with clear details. The description adds no additional meaning beyond the schema, such as examples or usage tips. Baseline 3 is appropriate when the schema does the heavy lifting.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the action ('Search for') and resource ('MCP servers in the MCPfinder registry'), providing a specific purpose. However, it doesn't explicitly differentiate from sibling tools like 'list_trending_servers' or 'get_mcp_server_details', which likely serve different functions (e.g., listing trending vs. detailed lookup).

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description offers no guidance on when to use this tool versus alternatives like 'list_trending_servers' or 'get_mcp_server_details'. It lacks context on scenarios where searching is preferred over listing or fetching details, leaving usage decisions ambiguous.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries the full burden of behavioral disclosure. While 'echoes back' implies a read-only operation that returns the input unchanged, it doesn't specify whether there are any side effects, rate limits, authentication requirements, or error conditions. The description is too minimal for a tool that might have behavioral nuances.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is perfectly concise at just 6 words. Every word earns its place: 'Test tool' establishes context, 'that echoes back' specifies the action, and 'the input' identifies the resource. There's zero waste or redundancy.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a simple echo tool with one parameter and no output schema, the description is adequate but minimal. It covers the basic purpose but lacks details about behavioral characteristics, usage context, or output format. Given the tool's simplicity, this is acceptable but not comprehensive.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The description mentions 'the input' but doesn't elaborate on parameter specifics beyond what the schema already provides. With 100% schema description coverage (the 'message' parameter is fully documented in the schema), the description adds minimal value. This meets the baseline expectation when the schema does the heavy lifting.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose with a specific verb ('echoes back') and resource ('the input'), making it immediately understandable. However, it doesn't distinguish this test tool from potential sibling tools that might also perform echo operations, which prevents a perfect score.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus alternatives. While it's labeled as a 'Test tool', there's no explicit mention of when it should be used, what testing scenarios it supports, or how it differs from the three sibling tools listed (get_mcp_server_details, list_trending_servers, search_mcp_servers).

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.